State Space Search


State Space Search
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State Space Search


State Space Search
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Author : Weixiong Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

State Space Search written by Weixiong Zhang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory, and it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two successful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions quickly, and the second is forward estimation for constructing more informative evaluation functions.



State Space Search


State Space Search
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-06-28

State Space Search written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-28 with Computers categories.


What Is State Space Search State space search is a technique that is employed in the field of computer science, particularly artificial intelligence (AI), in which consecutive configurations or states of an instance are explored, with the objective of finding a goal state with the desired feature. The term "state space search" comes from the phrase "state space," which refers to the space in which the process takes place. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: State Space Search Chapter 2: Brute-Force Search Chapter 3: Heuristic in Computer Science Chapter 4: Local Search Optimization Chapter 5: Game Tree Chapter 6: Constraint Satisfaction Problem Chapter 7: Adversarial Search Chapter 8: Markov Decision Process Chapter 9: Reinforcement Learning Chapter 10: Combinatorial search (II) Answering the public top questions about state space search. (III) Real world examples for the usage of state space search in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of state space search' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of state space search.



Artificial Intelligence Through Search


Artificial Intelligence Through Search
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Author : Chris Thornton
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Artificial Intelligence Through Search written by Chris Thornton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


This is an important textbook on artificial intelligence that uses the unifying thread of search to bring together most of the major techniques used in symbolic artificial intelligence. The authors, aware of the pitfalls of being too general or too academic, have taken a practical approach in that they include program code to illustrate their ideas. Furthermore, code is offered in both POP-11 and Prolog, thereby giving a dual perspective, highlighting the merits of these languages. Each chapter covers one technique and divides up into three sections: a section which introduces the technique (and its usual applications) andsuggests how it can be understood as a variant/generalisation of search; a section which developed a `low'-level (POP-11) implementation; a section which develops a high-level (Prolog) implementation of the technique. The authors also include useful notes on alternative treatments to the material, further reading and exercises. As a practical book it will be welcomed by a wide audience including, those already experienced in AI, students with some background in programming who are taking an introductory course in AI, and lecturers looking for a precise, professional and practical text book to use in their AI courses. About the authors: Dr Christopher Thornton has a BA in Economics, an Sc in Computer Science and a DPhil in Artificial Intelligence. Formerly a lecturer in the Department of AI at the University of Edinburgh, he is now a lecturer in AI in the School of Cognitive and Computing Sciences at the University of Sussex. Professor Benedict du Boulay has a BSc in Physics and a PhD in Artificial Intelligence. Previously a lecturer in the Department of Computing Science at the University of Aberdeen he is currently Professor of Artificial Intelligence, also in the School of Cognitive and Computing Sciences, University of Sussex.



Heuristic Search


Heuristic Search
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Author : Stefan Edelkamp
language : en
Publisher: Elsevier
Release Date : 2011-05-31

Heuristic Search written by Stefan Edelkamp and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-31 with Computers categories.


Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. Provides real-world success stories and case studies for heuristic search algorithms Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units



State Space Grids


State Space Grids
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Author : Tom Hollenstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-28

State Space Grids written by Tom Hollenstein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-28 with Psychology categories.


Human development from birth through adulthood is a complex interplay of many interacting forces. Children’s internal processes are manifest in behaviors that are sculpted by their experiences, most notably with primary caregivers. Because the discipline of psychology explores human behavior and cognition, the techniques employed for developmental analysis must be able to describe, depict, and quantify these complex processes. State Space Grids provides the framework, basic method, rationale, and advanced techniques for translating the behavior of children, adolescents, and parents into visible, traceable data. This seminar-between-covers takes readers step by step from conceptualization through implementation of projects, with examples from a range of current research within and outside child development. Links are included for the GridWare software program and related user resources. And although state space grids need not be used only to analyze dynamic systems, they serve as an excellent tool for honing systemic thinking. Key coverage in this volume includes: Dynamic systems and the origins of state space grids. The state of research using state space grids. Introducing GridWare and how it works. How to use state space grids, from idea through finished project. Within-grid and between-grid analysis. Conducting advanced analysis. State Space Grids is an essential reference for researchers across such disciplines as psychology, neuroscience, economics, computer science, and agricultural science.



State Space Modeling Of Time Series


State Space Modeling Of Time Series
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Author : Masanao Aoki
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

State Space Modeling Of Time Series written by Masanao Aoki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Business & Economics categories.


model's predictive capability? These are some of the questions that need to be answered in proposing any time series model construction method. This book addresses these questions in Part II. Briefly, the covariance matrices between past data and future realizations of time series are used to build a matrix called the Hankel matrix. Information needed for constructing models is extracted from the Hankel matrix. For example, its numerically determined rank will be the di mension of the state model. Thus the model dimension is determined by the data, after balancing several sources of error for such model construction. The covariance matrix of the model forecasting error vector is determined by solving a certain matrix Riccati equation. This matrix is also the covariance matrix of the innovation process which drives the model in generating model forecasts. In these model construction steps, a particular model representation, here referred to as balanced, is used extensively. This mode of model representation facilitates error analysis, such as assessing the error of using a lower dimensional model than that indicated by the rank of the Hankel matrix. The well-known Akaike's canonical correlation method for model construc tion is similar to the one used in this book. There are some important differ ences, however. Akaike uses the normalized Hankel matrix to extract canonical vectors, while the method used in this book does not normalize the Hankel ma trix.



Handbook Of Parallel Constraint Reasoning


Handbook Of Parallel Constraint Reasoning
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Author : Youssef Hamadi
language : en
Publisher: Springer
Release Date : 2018-04-05

Handbook Of Parallel Constraint Reasoning written by Youssef Hamadi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-05 with Computers categories.


This is the first book presenting a broad overview of parallelism in constraint-based reasoning formalisms. In recent years, an increasing number of contributions have been made on scaling constraint reasoning thanks to parallel architectures. The goal in this book is to overview these achievements in a concise way, assuming the reader is familiar with the classical, sequential background. It presents work demonstrating the use of multiple resources from single machine multi-core and GPU-based computations to very large scale distributed execution platforms up to 80,000 processing units. The contributions in the book cover the most important and recent contributions in parallel propositional satisfiability (SAT), maximum satisfiability (MaxSAT), quantified Boolean formulas (QBF), satisfiability modulo theory (SMT), theorem proving (TP), answer set programming (ASP), mixed integer linear programming (MILP), constraint programming (CP), stochastic local search (SLS), optimal path finding with A*, model checking for linear-time temporal logic (MC/LTL), binary decision diagrams (BDD), and model-based diagnosis (MBD). The book is suitable for researchers, graduate students, advanced undergraduates, and practitioners who wish to learn about the state of the art in parallel constraint reasoning.



Identifiability Of State Space Models


Identifiability Of State Space Models
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Author : E. Walter
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-07

Identifiability Of State Space Models written by E. Walter and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-07 with Mathematics categories.




State Space Search Models For Discrete Optimization Knapsack Algorithms And Related Problems


State Space Search Models For Discrete Optimization Knapsack Algorithms And Related Problems
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Author : Machiel Frederick Kruger
language : en
Publisher:
Release Date : 1998

State Space Search Models For Discrete Optimization Knapsack Algorithms And Related Problems written by Machiel Frederick Kruger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.




Search In Artificial Intelligence


Search In Artificial Intelligence
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Author : Leveen Kanal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Search In Artificial Intelligence written by Leveen Kanal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Search is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.